Comparing UAV-Based Technologies and RGB-D Reconstruction Methods for Plant Height and Biomass Monitoring on Grass Ley.

Pastures are botanically diverse and difficult to characterize. Digital modeling of pasture biomass and quality by non-destructive methods can provide highly valuable support for decision-making. This study aimed to evaluate aerial and on-ground methods to characterize grass ley fields, estimating plant height, biomass and volume, using digital grass models. Two fields were sampled, one timothy-dominant and the other ryegrass-dominant. Both sensing systems allowed estimation of biomass, volume and plant height, which were compared with ground truth, also taking into consideration basic economical aspects. To obtain ground-truth data for validation, 10 plots of 1 m² were manually and destructively sampled on each field. The studied systems differed in data resolution, thus in estimation capability. There was a reasonably good agreement between the UAV-based, the RGB-D-based estimates and the manual height measurements on both fields. RGB-D-based estimation correlated well with ground truth of plant height ( R 2 > 0.80 ) for both fields, and with dry biomass ( R 2 = 0.88 ), only for the timothy field. RGB-D-based estimation of plant volume for ryegrass showed a high agreement ( R 2 = 0.87 ). The UAV-based system showed a weaker estimation capability for plant height and dry biomass ( R 2 < 0.6 ). UAV-systems are more affordable, easier to operate and can cover a larger surface. On-ground techniques with RGB-D cameras can produce highly detailed models, but with more variable results than UAV-based models. On-ground RGB-D data can be effectively analysed with open source software, which is a cost reduction advantage, compared with aerial image analysis. Since the resolution for agricultural operations does not need fine identification the end-details of the grass plants, the use of aerial platforms could result a better option in grasslands.

Modelling CO2 and CH4 emissions from drained peatlands with grass cultivation by the BASGRA-BGC model.

Cultivated peatlands under drainage practices contribute significant carbon losses from agricultural sector in the Nordic countries. In this research, we developed the BASGRA-BGC model coupled with hydrological, soil carbon decomposition and methane modules to simulate the dynamic of water table level (WTL), carbon dioxide (CO2) and methane (CH4) emissions for cultivated peatlands. The field measurements from four experimental sites in Finland, Denmark and Norway were used to validate the predictive skills of this novel model under different WTL management practices, climatic conditions and soil properties. Compared with daily observations, the model performed well in terms of RMSE (Root Mean Square Error; 0.06-0.11 m, 1.22-2.43 gC/m2/day, and 0.002-0.330 kgC/ha/day for WTL, CO2 and CH4, respectively), NRMSE (Normalized Root Mean Square Error; 10.3-18.3%, 13.0-18.6%, 15.3-21.9%) and Pearson's r (Pearson correlation coefficient; 0.60-0.91, 0.76-0.88, 0.33-0.80). The daily/seasonal variabilities were therefore captured and the aggregated results corresponded well with annual estimations. We further provided an example on the model's potential use in improving the WTL management to mitigate CO2 and CH4 emissions while maintaining grass production. At all study sites, the simulated WTLs and carbon decomposition rates showed a significant negative correlation. Therefore, controlling WTL could effectively reduce carbon losses. However, given the highly diverse carbon decomposition rates within individual WTLs, adding indicators (e.g. soil moisture and peat quality) would improve our capacity to assess the effectiveness of specific mitigation practices such as WTL control and rewetting.

On the relative magnitudes of photosynthesis, respiration, growth and carbon storage in vegetation.

BACKGROUND AND AIMS: The carbon balance of vegetation is dominated by the two large fluxes of photosynthesis (P) and respiration (R). Mechanistic models have attempted to simulate the two fluxes separately, each with their own set of internal and external controls. This has led to model predictions where environmental change causes R to exceed P, with consequent dieback of vegetation. However, empirical evidence suggests that the R : P ratio is constrained to a narrow range of about 0.4-0.5. Physiological explanations for the narrow range are not conclusive. The aim of this work is to introduce a novel perspective by theoretical study of the quantitative relationship between the four carbon fluxes of P, R, growth and storage (or its inverse, remobilization). METHODS: Starting from the law of conservation of mass - in this case carbon - equations are derived for the relative magnitudes of all carbon fluxes, which depend on only two parameters: the R : P ratio and the relative rate of storage of carbon in remobilizable reserves. The equations are used to explain observed flux ratios and to analyse incomplete data sets of carbon fluxes. KEY RESULTS: The storage rate is shown to be a freely varying parameter, whereas R : P is narrowly constrained. This explains the constancy of the ratio reported in the literature. With the information thus gained, a data set of R and P in grassland was analysed, and flux estimates could be derived for the periods after cuts in which plant growth is dominated by remobilization before photosynthesis takes over. CONCLUSIONS: It is concluded that the relative magnitudes of photosynthesis, respiration, growth and substrate storage are indeed tightly constrained, but because of mass conservation rather than for physiological reasons. This facilitates analysis of incomplete data sets. Mechanistic models, as the embodiment of physiological mechanisms, need to show consistency with the constraints.

Weed suppression greatly increased by plant diversity in intensively managed grasslands: A continental-scale experiment.

Grassland diversity can support sustainable intensification of grassland production through increased yields, reduced inputs and limited weed invasion. We report the effects of diversity on weed suppression from 3 years of a 31-site continental-scale field experiment.At each site, 15 grassland communities comprising four monocultures and 11 four-species mixtures based on a wide range of species' proportions were sown at two densities and managed by cutting. Forage species were selected according to two crossed functional traits, "method of nitrogen acquisition" and "pattern of temporal development".Across sites, years and sown densities, annual weed biomass in mixtures and monocultures was 0.5 and 2.0 t  DM ha-1 (7% and 33% of total biomass respectively). Over 95% of mixtures had weed biomass lower than the average of monocultures, and in two-thirds of cases, lower than in the most suppressive monoculture (transgressive suppression). Suppression was significantly transgressive for 58% of site-years. Transgressive suppression by mixtures was maintained across years, independent of site productivity.Based on models, average weed biomass in mixture over the whole experiment was 52% less (95% confidence interval: 30%-75%) than in the most suppressive monoculture. Transgressive suppression of weed biomass was significant at each year across all mixtures and for each mixture.Weed biomass was consistently low across all mixtures and years and was in some cases significantly but not largely different from that in the equiproportional mixture. The average variability (standard deviation) of annual weed biomass within a site was much lower for mixtures (0.42) than for monocultures (1.77). Synthesis and applications. Weed invasion can be diminished through a combination of forage species selected for complementarity and persistence traits in systems designed to reduce reliance on fertiliser nitrogen. In this study, effects of diversity on weed suppression were consistently strong across mixtures varying widely in species' proportions and over time. The level of weed biomass did not vary greatly across mixtures varying widely in proportions of sown species. These diversity benefits in intensively managed grasslands are relevant for the sustainable intensification of agriculture and, importantly, are achievable through practical farm-scale actions.

Vernalization Requirement and the Chromosomal VRN1-Region can Affect Freezing Tolerance and Expression of Cold-Regulated Genes in Festuca pratensis.

Plants adapted to cold winters go through annual cycles of gain followed by loss of freezing tolerance (cold acclimation and deacclimation). Warm spells during winter and early spring can cause deacclimation, and if temperatures drop, freezing damage may occur. Many plants are vernalized during winter, a process making them competent to flower in the following summer. In winter cereals, a coincidence in the timing of vernalization saturation, deacclimation, downregulation of cold-induced genes, and reduced ability to reacclimate, occurs under long photoperiods and is under control of the main regulator of vernalization requirement in cereals, VRN1, and/or closely linked gene(s). Thus, the probability of freezing damage after a warm spell may depend on both vernalization saturation and photoperiod. We investigated the role of vernalization and the VRN1-region on freezing tolerance of meadow fescue (Festuca pratensis Huds.), a perennial grass species. Two F2 populations, divergently selected for high and low vernalization requirement, were studied. Each genotype was characterized for the copy number of one of the four parental haplotypes of the VRN1-region. Clonal plants were cold acclimated for 2 weeks or vernalized/cold acclimated for a total of 9 weeks, after which the F2 populations reached different levels of vernalization saturation. Vernalized and cold acclimated plants were deacclimated for 1 week and then reacclimated for 2 weeks. All treatments were given at 8 h photoperiod. Flowering response, freezing tolerance and expression of the cold-induced genes VRN1, MADS3, CBF6, COR14B, CR7 (BLT14), LOS2, and IRI1 was measured. We found that some genotypes can lose some freezing tolerance after vernalization and a deacclimation-reacclimation cycle. The relationship between vernalization and freezing tolerance was complex. We found effects of the VRN1-region on freezing tolerance in plants cold acclimated for 2 weeks, timing of heading after 9 weeks of vernalization, expression of COR14B, CBF6, and LOS2 in vernalized and/or deacclimated treatments, and restoration of freezing tolerance during reacclimation. While expression of VRN1, COR14B, CBF6, LOS2, and IRI1 was correlated, CR7 was associated with vernalization requirement by other mechanisms, and appeared to play a role in freezing tolerance in reacclimated plants.

Key challenges and priorities for modelling European grasslands under climate change.

Grassland-based ruminant production systems are integral to sustainable food production in Europe, converting plant materials indigestible to humans into nutritious food, while providing a range of environmental and cultural benefits. Climate change poses significant challenges for such systems, their productivity and the wider benefits they supply. In this context, grassland models have an important role in predicting and understanding the impacts of climate change on grassland systems, and assessing the efficacy of potential adaptation and mitigation strategies. In order to identify the key challenges for European grassland modelling under climate change, modellers and researchers from across Europe were consulted via workshop and questionnaire. Participants identified fifteen challenges and considered the current state of modelling and priorities for future research in relation to each. A review of literature was undertaken to corroborate and enrich the information provided during the horizon scanning activities. Challenges were in four categories relating to: 1) the direct and indirect effects of climate change on the sward 2) climate change effects on grassland systems outputs 3) mediation of climate change impacts by site, system and management and 4) cross-cutting methodological issues. While research priorities differed between challenges, an underlying theme was the need for accessible, shared inventories of models, approaches and data, as a resource for stakeholders and to stimulate new research. Developing grassland models to effectively support efforts to tackle climate change impacts, while increasing productivity and enhancing ecosystem services, will require engagement with stakeholders and policy-makers, as well as modellers and experimental researchers across many disciplines. The challenges and priorities identified are intended to be a resource 1) for grassland modellers and experimental researchers, to stimulate the development of new research directions and collaborative opportunities, and 2) for policy-makers involved in shaping the research agenda for European grassland modelling under climate change.

Overwintering of herbaceous plants in a changing climate. Still more questions than answers.

The increase in surface temperature of the Earth indicates a lower risk of exposure for temperate grassland and crop to extremely low temperatures. However, the risk of low winter survival rate, especially in higher latitudes may not be smaller, due to complex interactions among different environmental factors. For example, the frequency, degree and length of extreme winter warming events, leading to snowmelt during winter increased, affecting the risks of anoxia, ice encasement and freezing of plants not covered with snow. Future climate projections suggest that cold acclimation will occur later in autumn, under shorter photoperiod and lower light intensity, which may affect the energy partitioning between the elongation growth, accumulation of organic reserves and cold acclimation. Rising CO2 levels may also disturb the cold acclimation process. Predicting problems with winter pathogens is also very complex, because climate change may greatly influence the pathogen population and because the plant resistance to these pathogens is increased by cold acclimation. All these factors, often with contradictory effects on winter survival, make plant overwintering viability under future climates an open question. Close cooperation between climatologists, ecologists, plant physiologists, geneticists and plant breeders is strongly required to predict and prevent possible problems.